diff --git a/extensions/chaeo/batch_jobs/proj0004-exp0038-fixed.py b/extensions/chaeo/batch_jobs/proj0004-exp0038-fixed.py
index 6c85309040c09637899cdd43f75846b188c7d3f9..9ad9208e1d9b8f8d31e475872db982c864c9fcc0 100644
--- a/extensions/chaeo/batch_jobs/proj0004-exp0038-fixed.py
+++ b/extensions/chaeo/batch_jobs/proj0004-exp0038-fixed.py
@@ -2,6 +2,7 @@ from pathlib import Path
from model_server.util import autonumber_new_directory, get_matching_files, loop_workflow
from extensions.chaeo.workflows import export_patches_from_multichannel_zstack
+from extensions.ilastik.models import IlastikPixelClassifierModel
if __name__ == '__main__':
where_czi = 'z:/rhodes/projects/proj0004-marine-photoactivation/data/exp0038/AutoMic/20230906-163415/Selection'
@@ -13,12 +14,11 @@ if __name__ == '__main__':
px_ilp = Path.home() / 'model-server' / 'ilastik' / 'AF405-bodies_boundaries.ilp'
params = {
- 'ilastik_project_file': px_ilp.__str__(),
'pxmap_threshold': 0.25,
- 'pixel_class': 0,
- 'zmask_channel': 0,
+ 'pxmap_foreground_channel': 0,
+ 'segmentation_channel': 0,
'patches_channel': 4,
- 'mask_type': 'boxes',
+ 'zmask_type': 'boxes',
'zmask_filters': {'area': (1e3, 1e8)},
'zmask_expand_box_by': (128, 3),
'export_pixel_probabilities': False,
@@ -35,7 +35,9 @@ if __name__ == '__main__':
input_files,
where_output,
export_patches_from_multichannel_zstack,
+ [IlastikPixelClassifierModel(params={'project_file': Path(px_ilp)})],
params,
+ catch_and_continue=False,
)
print('Finished')
\ No newline at end of file
diff --git a/extensions/chaeo/workflows.py b/extensions/chaeo/workflows.py
index 21880fed686bf50668d2ee805004c455c9d11870..597475f927d155e181d20f550aa76b24d43f4e35 100644
--- a/extensions/chaeo/workflows.py
+++ b/extensions/chaeo/workflows.py
@@ -1,5 +1,5 @@
from pathlib import Path
-from typing import Dict
+from typing import Dict, List
from uuid import uuid4
import numpy as np
@@ -11,22 +11,77 @@ from extensions.ilastik.models import IlastikPixelClassifierModel
from extensions.chaeo.annotators import draw_boxes_on_3d_image
from extensions.chaeo.products import export_patches_from_zstack, export_patch_masks_from_zstack, export_multichannel_patches_from_zstack
from extensions.chaeo.zmask import build_zmask_from_object_mask, project_stack_from_focal_points
+from extensions.ilastik.models import IlastikPixelClassifierModel
+
from model_server.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
+from model_server.models import Model
from model_server.process import rescale
from model_server.workflows import Timer
+def get_zmask_meta(
+ input_file_path: str,
+ ilastik_pixel_classifier: IlastikPixelClassifierModel,
+ segmentation_channel: int,
+ pxmap_threshold: float,
+ pxmap_foreground_channel: int = 0,
+ zmask_zindex: int = None,
+ zmask_clip: int = None,
+ zmask_expand_box_by: int = None,
+ zmask_filters: Dict = None,
+ zmask_type: str = 'boxes',
+
+
+) -> Dict:
+ ti = Timer()
+ stack = generate_file_accessor(Path(input_file_path))
+ fstem = Path(input_file_path).stem
+ ti.click('file_input')
+
+ # MIP if no zmask z-index is given, then classify pixels
+ if isinstance(zmask_zindex, int):
+ assert 0 < zmask_zindex < stack.nz
+ zmask_data = stack.get_one_channel_data(channel=segmentation_channel).data[:, :, :, zmask_zindex]
+ else:
+ zmask_data = stack.get_one_channel_data(channel=segmentation_channel).data.max(axis=-1, keepdims=True)
+ if zmask_clip:
+ zmask_data = rescale(zmask_data, zmask_clip)
+ mip = InMemoryDataAccessor(
+ zmask_data,
+ )
+ pxmap, _ = ilastik_pixel_classifier.infer(mip)
+ ti.click('infer_pixel_probability')
+
+ obmask = InMemoryDataAccessor(
+ pxmap.data > pxmap_threshold
+ )
+ ti.click('threshold_pixel_mask')
+
+ # make zmask
+ zmask, zmask_meta, df, interm = build_zmask_from_object_mask(
+ obmask.get_one_channel_data(pxmap_foreground_channel),
+ stack.get_one_channel_data(segmentation_channel),
+ mask_type=zmask_type,
+ filters=zmask_filters,
+ expand_box_by=zmask_expand_box_by,
+ )
+ zmask_acc = InMemoryDataAccessor(zmask)
+ ti.click('generate_zmasks')
+
+ return ti, stack, fstem, pxmap, zmask, zmask_meta, df, interm
+
+
# TODO: unpack and validate inputs
def export_patches_from_multichannel_zstack(
input_file_path: str,
output_folder_path: str,
- ilastik_project_file: str,
+ models: List[Model],
pxmap_threshold: float,
- pixel_class: int,
- zmask_channel: int,
+ pxmap_foreground_channel: int,
+ segmentation_channel: int,
patches_channel: int,
zmask_zindex: int = None, # None for MIP,
- rescale_zmask_clip: int = None,
- mask_type: str = 'boxes',
+ zmask_clip: int = None,
+ zmask_type: str = 'boxes',
zmask_filters: Dict = None,
zmask_expand_box_by: int = None,
export_pixel_probabilities=True,
@@ -41,27 +96,20 @@ def export_patches_from_multichannel_zstack(
rgb_overlay_channels=(None, None, None),
rgb_overlay_weights=(1.0, 1.0, 1.0),
) -> Dict:
- ti = Timer()
- stack = generate_file_accessor(Path(input_file_path))
- fstem = Path(input_file_path).stem
- ti.click('file_input')
+ pixel_classifier = models[0]
- # MIP and classify pixels
- if isinstance(zmask_zindex, int):
- assert 0 < zmask_zindex < stack.nz
- zmask_data = stack.get_one_channel_data(channel=zmask_channel).data[:, :, :, zmask_zindex]
- else:
- zmask_data = stack.get_one_channel_data(channel=zmask_channel).data.max(axis=-1, keepdims=True)
- if rescale_zmask_clip:
- zmask_data = rescale(zmask_data, rescale_zmask_clip)
- mip = InMemoryDataAccessor(
- zmask_data,
- )
- px_model = IlastikPixelClassifierModel(
- params={'project_file': Path(ilastik_project_file)}
+ ti, stack, fstem, pxmap, zmask, zmask_meta, df, interm = get_zmask_meta(
+ input_file_path,
+ pixel_classifier,
+ segmentation_channel,
+ pxmap_threshold,
+ pxmap_foreground_channel=pxmap_foreground_channel,
+ zmask_zindex=zmask_zindex,
+ zmask_clip=zmask_clip,
+ zmask_expand_box_by=zmask_expand_box_by,
+ zmask_filters=zmask_filters,
+ zmask_type=zmask_type,
)
- pxmap, _ = px_model.infer(mip)
- ti.click('infer_pixel_probability')
if export_pixel_probabilities:
write_accessor_data_to_file(
@@ -70,22 +118,6 @@ def export_patches_from_multichannel_zstack(
)
ti.click('export_pixel_probability')
- obmask = InMemoryDataAccessor(
- pxmap.data > pxmap_threshold
- )
- ti.click('threshold_pixel_mask')
-
- # make zmask
- zmask, zmask_meta, df, interm = build_zmask_from_object_mask(
- obmask.get_one_channel_data(pixel_class),
- stack.get_one_channel_data(zmask_channel),
- mask_type=mask_type,
- filters=zmask_filters,
- expand_box_by=zmask_expand_box_by,
- )
- zmask_acc = InMemoryDataAccessor(zmask)
- ti.click('generate_zmasks')
-
if export_3d_patches:
files = export_patches_from_zstack(
Path(output_folder_path) / '3d_patches',
@@ -168,7 +200,7 @@ def export_patches_from_multichannel_zstack(
)
return {
- 'pixel_model_id': px_model.model_id,
+ 'pixel_model_id': pixel_classifier.model_id,
'input_filepath': input_file_path,
'number_of_objects': len(zmask_meta),
'pixeL_scale_in_micrometers': stack.pixel_scale_in_micrometers,
diff --git a/extensions/chaeo/zmask.py b/extensions/chaeo/zmask.py
index cc04a7282dc9756561bbcd72cd6dd560d4c1fd60..e9967e70630820d876d49a0b21a2bbe39d2cf082 100644
--- a/extensions/chaeo/zmask.py
+++ b/extensions/chaeo/zmask.py
@@ -11,7 +11,7 @@ def build_zmask_from_object_mask(
obmask: GenericImageDataAccessor,
zstack: GenericImageDataAccessor,
filters=None,
- mask_type='contour',
+ mask_type='contours',
expand_box_by=(0, 0),
):
"""
diff --git a/model_server/util.py b/model_server/util.py
index 8bc071ab056570a594658a0be4fa99eeb9c875dd..1cc33753dbe477e3ddff686f2a5459a93386b7bb 100644
--- a/model_server/util.py
+++ b/model_server/util.py
@@ -1,10 +1,12 @@
from pathlib import Path
import re
from time import localtime, strftime
+from typing import List
import pandas as pd
from model_server.accessors import InMemoryDataAccessor, write_accessor_data_to_file
+from model_server.models import Model
def autonumber_new_directory(where: str, prefix: str) -> str:
"""
@@ -75,6 +77,7 @@ def loop_workflow(
files: list,
output_folder_path: str,
workflow_func: callable,
+ models: List[Model],
params: dict,
export_batch_csvs: bool = True,
write_intermediate_products: bool = True,
@@ -95,6 +98,7 @@ def loop_workflow(
export_kwargs = {
'input_file_path': ff,
'output_folder_path': output_folder_path,
+ 'models': models,
**params,
}